Cost or Benefit? Using Pond Levellers to Mitigate Human-Beaver Conflicts
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Human-wildlife conflicts can create social, economic and environmental issues within protected areas and rural municipalities. Increasingly, parks and rural municipalities are tasked with managing these conflicts, despite sometimes unclear jurisdictional and political boundaries. Wildlife, as a public good, is also highly valued by Albertans for recreational and aesthetic reasons. For this study, we developed a cost-benefit analysis to assess the management of human-beaver conflicts within the Cooking Lake/Blackfoot Provincial Recreation Area and Beaver County. Through the installation of pond-levellers and an assessment of their efficacy over several years we were able compare traditional and alternative management approaches. This research provides greater insight into how wildlife are managed at a local park or municipal level and how well these management actions perform relative to economic and ecological metrics. *Indicates faculty mentor
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it